title: A novel approach to improve health status measurement  in observational claims-based studies of cancer treatment  and outcomes.
abstract: OBJECTIVE
  To develop and provide initial validation for amultivariate, claims-based prediction model for disability status (DS), a proxymeasure of performance status (PS), among older adults. The model was designed to augment information on health status at the point of cancer diagnosis in studies using insurance claims to examine cancer treatment and outcomes.
  
  
  METHODS
  We used data from the 2001–2005 Medicare Current Beneficiary Survey (MCBS), with observations randomly split into estimation and validation subsamples. We developed an algorithm linking self-reported functional status measures to a DS scale, a proxy for the Eastern Cooperative Oncology Group (ECOG) PS scale. The DS measure was dichotomized to focus on good [ECOG 0–2] versus poor [ECOG 3–4] PS. We identified potential claims-based predictors, and estimated multivariate logistic regression models, with poor DS as the dependent measure, using a stepwise approach to select the optimal model. Construct validity was tested by determining whether the predicted DS measure generated by the model was a significant predictor of survival within a validation sample from the MCBS.
  
  
  CONCLUSIONS
  One-tenth of the beneficiaries met the definition for poor DS. The base model yielded high sensitivity (0.79) and specificity (0.92); positive predictive value=48.3% and negative predictive value=97.8%, c-statistic=0.92 and good model calibration. Adjusted poor claims-based DS was associated with an increased hazard of death (HR=3.53, 95% CI 3.18, 3.92). The ability to assess DS should improve covariate control and reduce indication bias in observational studies of cancer treatment and outcomes based on insurance claims.
authors.forename: Amy J
authors.initials: AJ
authors.lastname: Davidoff
authors.forename: Ilene H
authors.initials: IH
authors.lastname: Zuckerman
authors.forename: Naimish
authors.initials: N
authors.lastname: Pandya
authors.forename: Franklin
authors.initials: F
authors.lastname: Hendrick
authors.forename: Xuehua
authors.initials: X
authors.lastname: Ke
authors.forename: Arti
authors.initials: A
authors.lastname: Hurria
authors.forename: Stuart M
authors.initials: SM
authors.lastname: Lichtman
authors.forename: Arif
authors.initials: A
authors.lastname: Hussain
authors.forename: Jonathan P
authors.initials: JP
authors.lastname: Weiner
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Edelman
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D004185:Disability Evaluation; D005260:Female; D006304:Health Status; D006306:Health Surveys; D006801:Humans; D007345:Insurance Claim Review; D008297:Male; D006278:Medicare; D015999:Multivariate Analysis; D009369:Neoplasms / Q000453:epidemiology*; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012680:Sensitivity and Specificity; D014481:United States / Q000453:epidemiology